Exploration

Efficient Exploration in Continuous-time Model-based Reinforcement Learning NeurIPS 2023 Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations NeurIPS 2023 Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning ICML 2023 MIMEx: Intrinsic Rewards from Masked Input Modeling NeurIPS 2023 Networked Restless Bandits with Positive Externalities AAAI 2023 Optimistic Active Exploration of Dynamical Systems NeurIPS 2023 Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning ICLR 2023 Reinforced Approximate Exploratory Data Analysis AAAI 2023 Thompson Exploration with Best Challenger Rule in Best Arm Identification ACML 2023 A First-Occupancy Representation for Reinforcement Learning ICLR 2022 A Mixture Of Surprises for Unsupervised Reinforcement Learning NeurIPS 2022 An Analysis of Ensemble Sampling NeurIPS 2022 Diversified Recommendations for Agents with Adaptive Preferences NeurIPS 2022 Exploration via Elliptical Episodic Bonuses NeurIPS 2022 Exploration via Planning for Information about the Optimal Trajectory NeurIPS 2022 Exploring through Random Curiosity with General Value Functions NeurIPS 2022 Fire Burns, Sword Cuts: Commonsense Inductive Bias for Exploration in Text-based Games ACL 2022 LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward NeurIPS 2022 Near-Optimal Randomized Exploration for Tabular Markov Decision Processes NeurIPS 2022 Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver ICLR 2022 Offline Reinforcement Learning as Anti-exploration AAAI 2022 On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL NeurIPS 2022 Optimistic Initialization for Exploration in Continuous Control AAAI 2022 Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity NeurIPS 2022 Better Bounds on the Adaptivity Gap of Influence Maximization under Full-adoption Feedback AAAI 2021